Prerequisite: Knowledge of data processing, foundational knowledge about machine learning and deep learning.

Big data has transformed our thinking like never before. The ability for us to look for all data across the entire ecosystem means we can be unbridled in our discovery journey for data, which can be connected and analyzed on demand. How does this magic happen? Where are the layers of data management and processing? Who delivers the ability to connect, analyze, and visualize data? How can we implement a program to deliver these outcomes? This session is geared and designed to answer these questions and more.

You Will Learn

• The foundations of machine learning and deep learning
• To understand and decipher behaviors from a machine viewpoint
• To integrate search implementation theory with data for deep learning
• An introduction to TensorFlow, Caffe 2, and a library of open source algorithms
• How to implement machine and deep learning, including the processing techniques involved
• What analytics insights, outcomes, mashups, and KPIs are available
• How to visualize the results of machine and deep learning

Geared To

• Technical professionals, business professionals with analytical background